Analytics, Finance & Strategy

Key Responsibilities

• Build the relative-value measurement system: evolve our cross-product benchmark into a durable, trusted read on model and product value, spanning coding, agentic, and product-shaped tasks
• Inform pricing and packaging: construct task-cost approximations and price-elasticity estimates across differently priced products, and carry them into decisions
• Own launch and market analytics: run analytics around model launches, including capability-based revenue analyses and views of the broader market
• Deepen our market understanding: evaluate and integrate external datasets and research to strengthen our read on the market and how it's evolving
• Partner with Product Finance: take open-ended pricing, packaging, and positioning questions from vague ask to decision-grade answer
• Raise the bar: land narratives in executive forums and uplevel the team’s product-finance analytics practice by example

Minimum Qualifications

• Put shape around ambiguity: you’ve personally defined the measurement approach for questions nobody knew how to answer, without waiting for a fully specified ask
• Land narratives with executives: your analyses have changed pricing, product, or competitive decisions, and you can simplify for senior leaders without losing rigor
• Stay hands-on at senior scope: you still write the SQL and Python yourself, and you’d rather ship a defensible v1 with honest error bars than wait for perfect data
• Are inherently curious: you go one level deeper than asked and are energized by how fast models, products, and the market are moving
• Thrive amid shifting priorities: you juggle multiple fast-moving workstreams and stay effective when the plan changes weekly
• Work fluently with modern tooling: you’re strong at data visualization, use Claude and AI tools as force multipliers in analysis and BI, and can self-serve your own workflows across SQL, Python, dbt, and a cloud warehouse

Preferred Qualifications

• Experience designing evals or benchmarks for AI models or products
• Pricing and packaging analytics at scale, including elasticity estimation
• Market share estimation from imperfect third-party, panel, or survey data
• Fluency in the LLM model and product landscape
• Dimensional modeling and warehouse design experience (grain, SCDs, point-in-time correctness)
• Cloud platform experience (AWS, GCP) with orchestration, CI/CD for data, and testing/observability

Compensation & Benefits

• Annual Salary: $270,000—$320,000 USD
• Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.